Multiple Peak Points Research Articles

Thermoelectric power generation system intelligent Runge Kutta control: A performance analysis using processor in loop testing

As an emerging source of clean electrical power, Thermoelectric generation (TEG) finds its applications in heat removal and electricity generation as an efficient improvement tool for thermal devices utilizing fossil fuels. TEG exhibits low power density and its temperature distribution is usually non-uniform over thermal conductive surfaces. Due to the non-uniformity of heat flow and loose surface contact, non-uniform temperature distribution (NTD) appears on TEG surfaces and the TEG control problem becomes complex, multi-solution, nonlinear, and highly sensitive to operating conditions. The bypass diode activation of TEG systems streamlines the power flow in a string of series-connected modules, generating multiple peak points. Classical techniques fail to address these issues of multiple maxima and lose efficiency. To solve this problem, a novel SI-based optimization algorithm, Runge Kutta Method (RUN), is applied as MPPT control. To gauge the performance of the proposed controller several distinct case studies are used, including varying temperatures gradient, NTD, 24-hour thermal profile stochastic temperature, and experimental verification. Additionally, MPPT rating analysis, economic assessment, and statistical studies are done for comparison with other state-of-the-art control techniques. The minimum tracking and settling times have been improved by RUN to 180 ms. For the additional hardware implementation, the maximum levelized cost of energy (LCOE) is about 0.16 $kWh1.07¥kWh. The power tracking efficiency of RUN can be above 99 % with energy harvest improvements of 6.3 %.

Enhanced power generation for total‐cross‐tied PV array using simulated annealing under partial shading conditions

Shade phenomena affect the PV module's power output, introduce multiple peak points in PV characteristics, and shorten the expected life cycle of the module. In order to prevent this issue, PV modules should reconfigure, namely, altering the electrical connections between PV modules based on the irradiance without changing their physical locations. As a result, the shading effects can distribute over the array and increase power output. This paper proposed a novel reconfiguration technique based on the simulated annealing algorithm to distribute shading impacts on 9 × 9 total-cross-tied (TCT) PV array. In this work, the proposed algorithm produces a reconfigured connection matrix for 9 × 9 TCT array that can minimize the current differences in each row and improve the power output. Various shading conditions have been taken to investigate the proposed technique by obtained global maximum power point (GMPP), current at GMPP, power loss, fill-factor, and efficiency. Further, the performance of the proposed technique is validated with other existing reconfiguration methods under partial shadings. In comparison with existing methods, the result shows that the proposed simulated annealing enhanced the power generation of the TCT array under all shading patterns.

Enhanced performance metrics under shading conditions through experimental investigations

The phenomenon of partial shading adversely affects photovoltaic arrays, e.g. multiple peak points in P – V characteristic curves and reducing the output power. Array reconfiguration is the best and efficient way of alleviating the partial shading effects. Physical relocation of panels can be used as a practical solution to prevent shading problems by altering the physical location of panels by not changing its electrical circuit. In this study, a new reconfiguration technique named as Arrow Sudoku pattern is proposed for all the conventional configurations such as, series–parallel, bridge-link, honeycomb, and total cross-tied connections to mitigate the shading effects. The proposed approach is tested on a 6 × 6 Solar Photo-Voltaic (SPV) array for different groups of shading conditions. The results are simulated through MATLAB/Simulink and validated through hardware prototype using artificial shade blockers and the results show a good improvement in the diagnosis of output parameters for all the reconfiguration techniques in comparison with their initial configurations. Moreover, the disturbance caused in P – V characteristic curves by shading is eradicated by using this proposed technique.

An Algorithm for Enhanced Performance of Photovoltaic Array Under Partial Shading Condition

The partial shading on photovoltaic (PV) modules causes a reduction in generated power and multiple peak points in their electrical characteristics. If the number of shaded modules of two or more rows are different then electrical characteristics exhibit multiple peaks. Also, as the number of shaded modules in a row increases the generated power decreases. These two observations are the main idea of this paper. The algorithm proposed in this paper redistributes shaded modules to various rows such that each row gets the lowest possible number of shaded modules and thereby increases the generated power. This work discusses a condition to achieve an equal number of shaded modules in all rows for which there is only one peak in the electrical characteristics. For the case where this condition is not satisfied, there can only be two-row groups with a different number of shaded modules. However, each group is having the same number of shaded modules and so only two peaks in the electrical characteristics. The proposed algorithm is applicable to any mxn structure of PV arrays. Extensive simulations are carried out and the performance of the proposed algorithm is compared with existing methods for various shading patterns. The results show that the proposed method gives minimum power loss, better performance ratio, and a lesser number of peak points.

Genetic Algorithm Based PV Array Reconfiguration for Improving Power Output under Partial Shadings

The behavior of the Photovoltaic (PV) system may change with respect to climatic conditions. Partial shading is a significant one, the most prominent one, and the problem has been worked out so far in the literature. The impact of partial shading demolishes the PV power output and manifests multiple peak points in the PV characteristics. One of the most effective techniques suggested in the literature to overcome this issue is the electrical array reconfiguration. This paper proposed an electrical array reconfiguration method based on Genetic Algorithm (GA) for Total-Cross-Tied (TCT) array to minimize PSCs and increase power production. The physical positions of the modules in the TCT array are constant in this work, but their electrical connections are altered depending on levels of irradiance. The proposed algorithm produces a TCT array connection pattern, thus spreading shading effects over the array, and increasing the power output. This method is tested under different shading conditions on 6×6 size of array and compared with existing reconfiguration methods. The performance of the proposed method is also investigated through Shadow Loss (SL), Fill-Factor (FF), and Efficiency estimation.

Implementation and simulation analysis of GMPPT algorithm under partial shadow condition

Abstract Due to partial occlusion, the output power and voltage curves of PV arrays appear multiple peak points, which increase the difficulty of designing the maximum power tracking system. The limitations of the conventional GMPPT method under the partial shadow are analyzed, and the failure of the traditional optimization algorithm is obtained. The optimization algorithm with strong global search ability can be used to solve the problem. A quantum-behaved particle swarm optimization (QPSO) algorithm is proposed and the implementation process of the algorithm is given. Finally, the standard particle swarm optimization (PSO) algorithm is compared with QPSO. It shows that QPSO is more suitable for solving the photovoltaic MPPT questions under partial shadow, effectively improving the photovoltaic utilization and generating electricity.

Partial Shading Detection and Smooth Maximum Power Point Tracking of PV Arrays Under PSC

One of the most important issues in the operation of a photovoltaic (PV) system is extracting maximum power from the PV array, especially in partial shading condition (PSC). Under PSC, P–V characteristic of PV arrays will have multiple peak points, only one of which is global maximum. Conventional maximum power point tracking (MPPT) methods are not able to extract maximum power in this condition. In this paper, a novel two-stage MPPT method is presented to overcome this drawback. In the first stage, a method is proposed to determine the occurrence of PSC, and in the second stage, using a new algorithm that is based on ramp change of the duty cycle and continuous sampling from the P–V characteristic of the array, global maximum power point (MPP) of array is reached. Perturb and observe algorithm is then re-activated to trace small changes of the new MPP. Open-loop operation of the proposed method makes its implementation cheap and simple. The method is robust in the face of changing environmental conditions and array characteristics, and has minimum negative impact on the connected power system. Simulations in Matlab/Simulink and experimental results validate the performance of the proposed methods.

Experimental investigation of a multifunctional grid interactive photovoltaic system operating in partial shading conditions

In this study, a multifunctional grid interactive photovoltaic (PV) system working in partial shading conditions using a novel algorithm for tracking global peak power point (GPPP) is proposed. The system is capable of performing multiple functions like reactive power compensation and harmonic elimination besides injecting active power produced by PV array, into grid. The PV array is connected at the DC link of shunt active power filter via a DC–DC step-up converter whose switching is controlled by the proposed GPPP tracking algorithm. The proposed algorithm determines the global peak amongst multiple peak points on the power–voltage (P–V) curve under partially shaded condition without getting trapped at a local maximum. The algorithm determines the approximate location of global peak by sampling the complete P–V curve in larger steps at regular interval and then uses fuzzy logic for finding the real peak. This method gives faster convergence and minimum oscillations around the GPPP. The algorithm is capable of tracking the GPPP under uniform insolation as well as partially shaded condition. The outcomes of the simulation study carried out using MATLAB/SIMULINK show the effectiveness of a proposed multifunctional PV system using fuzzy logic controlled GPPP tracking algorithm. The experimental results authenticate the simulation study.

Experimental evaluation of a partially shaded photovoltaic system with a fuzzy logic‐based peak power tracking control strategy

Partial shading on photovoltaic (PV) array makes the task of operating the PV system at its peak power more complex due to multiple peak points on power–voltage (P–V) characteristic. Amongst multiple peaks, it is challenging to find global peak as there is a possibility of the system getting stuck at a local peak otherwise considerable loss of power may occur. In this study, experimental evaluation of a novel algorithm which tracks global peak is presented. The algorithm is capable of tracking the peak power under all partial shadowing and uniformly varying insolation conditions. The algorithm scans the entire P–V curve in larger steps by varying the duty cycle of DC–DC converter without missing any peak to determine approximate location of peak power point and then uses fuzzy logic to track the real global peak. The algorithm is verified through simulation and the results are validated through hardware implementation using TMS320F28335 digital signal processor. The experimental results match with the simulation results that justify the performance and robustness of the proposed algorithm for tracking global peak power when the PV array is partially shaded. The comparative evaluation of the proposed algorithm with conventional perturb and observe-based method is also carried out experimentally.